sqrt D (should all be same)

Percentage Accurate: 54.0% → 99.4%

Time: 5.2s

Alternatives: 6

Speedup: 2.0×

Specification

Math

\[\begin{array}{l} \\ \sqrt{2 \cdot {x}^{2}} \end{array} \]

FPCore

(FPCore (x) :precision binary64 (sqrt (* 2.0 (pow x 2.0))))

C

double code(double x) {
	return sqrt((2.0 * pow(x, 2.0)));
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = sqrt((2.0d0 * (x ** 2.0d0)))
end function

Java

public static double code(double x) {
	return Math.sqrt((2.0 * Math.pow(x, 2.0)));
}

Python

def code(x):
	return math.sqrt((2.0 * math.pow(x, 2.0)))

Julia

function code(x)
	return sqrt(Float64(2.0 * (x ^ 2.0)))
end

MATLAB

function tmp = code(x)
	tmp = sqrt((2.0 * (x ^ 2.0)));
end

Wolfram

code[x_] := N[Sqrt[N[(2.0 * N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]

Initial Program: 54.0% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \sqrt{2 \cdot {x}^{2}} \end{array} \]

FPCore

(FPCore (x) :precision binary64 (sqrt (* 2.0 (pow x 2.0))))

C

double code(double x) {
	return sqrt((2.0 * pow(x, 2.0)));
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = sqrt((2.0d0 * (x ** 2.0d0)))
end function

Java

public static double code(double x) {
	return Math.sqrt((2.0 * Math.pow(x, 2.0)));
}

Python

def code(x):
	return math.sqrt((2.0 * math.pow(x, 2.0)))

Julia

function code(x)
	return sqrt(Float64(2.0 * (x ^ 2.0)))
end

MATLAB

function tmp = code(x)
	tmp = sqrt((2.0 * (x ^ 2.0)));
end

Wolfram

code[x_] := N[Sqrt[N[(2.0 * N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]

Alternative 1: 99.4% accurate, 1.0× speedup

Math

\[\begin{array}{l} x_m = \left|x\right| \\ {\left(x\_m \cdot 4\right)}^{0.25} \cdot {x\_m}^{0.75} \end{array} \]

FPCore

x_m = (fabs.f64 x)
(FPCore (x_m) :precision binary64 (* (pow (* x_m 4.0) 0.25) (pow x_m 0.75)))

C

x_m = fabs(x);
double code(double x_m) {
	return pow((x_m * 4.0), 0.25) * pow(x_m, 0.75);
}

Fortran

x_m = abs(x)
real(8) function code(x_m)
    real(8), intent (in) :: x_m
    code = ((x_m * 4.0d0) ** 0.25d0) * (x_m ** 0.75d0)
end function

Java

x_m = Math.abs(x);
public static double code(double x_m) {
	return Math.pow((x_m * 4.0), 0.25) * Math.pow(x_m, 0.75);
}

Python

x_m = math.fabs(x)
def code(x_m):
	return math.pow((x_m * 4.0), 0.25) * math.pow(x_m, 0.75)

Julia

x_m = abs(x)
function code(x_m)
	return Float64((Float64(x_m * 4.0) ^ 0.25) * (x_m ^ 0.75))
end

MATLAB

x_m = abs(x);
function tmp = code(x_m)
	tmp = ((x_m * 4.0) ^ 0.25) * (x_m ^ 0.75);
end

Wolfram

x_m = N[Abs[x], $MachinePrecision]
code[x$95$m_] := N[(N[Power[N[(x$95$m * 4.0), $MachinePrecision], 0.25], $MachinePrecision] * N[Power[x$95$m, 0.75], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 56.3%

   \[\sqrt{2 \cdot {x}^{2}} \]
2. Step-by-step derivation

   1. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\left(2 \cdot {x}^{2}\right)\right) \]

   2. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left({x}^{2}\right)\right)\right) \]

   3. unpow2 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(x \cdot x\right)\right)\right) \]

   4. *-lowering-*.f64 56.3%

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{*.f64}\left(x, x\right)\right)\right) \]

3. Simplified 56.3%

   \[\leadsto \color{blue}{\sqrt{2 \cdot \left(x \cdot x\right)}} \]
4. Add Preprocessing
5. Step-by-step derivation

   1. pow1/2 N/A

      \[\leadsto {\left(2 \cdot \left(x \cdot x\right)\right)}^{\color{blue}{\frac{1}{2}}} \]

   2. rem-square-sqrt N/A

      \[\leadsto {\left(2 \cdot \left(\left(\sqrt{x} \cdot \sqrt{x}\right) \cdot x\right)\right)}^{\frac{1}{2}} \]

   3. pow1/2 N/A

      \[\leadsto {\left(2 \cdot \left(\left({x}^{\frac{1}{2}} \cdot \sqrt{x}\right) \cdot x\right)\right)}^{\frac{1}{2}} \]

   4. pow1/2 N/A

      \[\leadsto {\left(2 \cdot \left(\left({x}^{\frac{1}{2}} \cdot {x}^{\frac{1}{2}}\right) \cdot x\right)\right)}^{\frac{1}{2}} \]

   5. associate-*l* N/A

      \[\leadsto {\left(2 \cdot \left({x}^{\frac{1}{2}} \cdot \left({x}^{\frac{1}{2}} \cdot x\right)\right)\right)}^{\frac{1}{2}} \]

   6. associate-*r* N/A

      \[\leadsto {\left(\left(2 \cdot {x}^{\frac{1}{2}}\right) \cdot \left({x}^{\frac{1}{2}} \cdot x\right)\right)}^{\frac{1}{2}} \]

   7. unpow-prod-down N/A

      \[\leadsto {\left(2 \cdot {x}^{\frac{1}{2}}\right)}^{\frac{1}{2}} \cdot \color{blue}{{\left({x}^{\frac{1}{2}} \cdot x\right)}^{\frac{1}{2}}} \]

   8. unpow-prod-down N/A

      \[\leadsto {\left(2 \cdot {x}^{\frac{1}{2}}\right)}^{\frac{1}{2}} \cdot \left({\left({x}^{\frac{1}{2}}\right)}^{\frac{1}{2}} \cdot \color{blue}{{x}^{\frac{1}{2}}}\right) \]

   9. pow1/2 N/A

      \[\leadsto {\left(2 \cdot {x}^{\frac{1}{2}}\right)}^{\frac{1}{2}} \cdot \left({\left(\sqrt{x}\right)}^{\frac{1}{2}} \cdot {x}^{\frac{1}{2}}\right) \]

   10. sqrt-pow2 N/A

       \[\leadsto {\left(2 \cdot {x}^{\frac{1}{2}}\right)}^{\frac{1}{2}} \cdot \left({x}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\color{blue}{x}}^{\frac{1}{2}}\right) \]

   11. *-commutative N/A

       \[\leadsto {\left(2 \cdot {x}^{\frac{1}{2}}\right)}^{\frac{1}{2}} \cdot \left({x}^{\frac{1}{2}} \cdot \color{blue}{{x}^{\left(\frac{\frac{1}{2}}{2}\right)}}\right) \]

   12. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\left({\left(2 \cdot {x}^{\frac{1}{2}}\right)}^{\frac{1}{2}}\right), \color{blue}{\left({x}^{\frac{1}{2}} \cdot {x}^{\left(\frac{\frac{1}{2}}{2}\right)}\right)}\right) \]

6. Applied egg-rr 48.6%

   \[\leadsto \color{blue}{{\left(x \cdot 4\right)}^{0.25} \cdot {x}^{0.75}} \]
7. Add Preprocessing

Alternative 2: 99.5% accurate, 1.0× speedup

Math

\[\begin{array}{l} x_m = \left|x\right| \\ \frac{\sqrt{x\_m}}{{\left(x\_m \cdot 2\right)}^{-0.5}} \end{array} \]

FPCore

x_m = (fabs.f64 x)
(FPCore (x_m) :precision binary64 (/ (sqrt x_m) (pow (* x_m 2.0) -0.5)))

C

x_m = fabs(x);
double code(double x_m) {
	return sqrt(x_m) / pow((x_m * 2.0), -0.5);
}

Fortran

x_m = abs(x)
real(8) function code(x_m)
    real(8), intent (in) :: x_m
    code = sqrt(x_m) / ((x_m * 2.0d0) ** (-0.5d0))
end function

Java

x_m = Math.abs(x);
public static double code(double x_m) {
	return Math.sqrt(x_m) / Math.pow((x_m * 2.0), -0.5);
}

Python

x_m = math.fabs(x)
def code(x_m):
	return math.sqrt(x_m) / math.pow((x_m * 2.0), -0.5)

Julia

x_m = abs(x)
function code(x_m)
	return Float64(sqrt(x_m) / (Float64(x_m * 2.0) ^ -0.5))
end

MATLAB

x_m = abs(x);
function tmp = code(x_m)
	tmp = sqrt(x_m) / ((x_m * 2.0) ^ -0.5);
end

Wolfram

x_m = N[Abs[x], $MachinePrecision]
code[x$95$m_] := N[(N[Sqrt[x$95$m], $MachinePrecision] / N[Power[N[(x$95$m * 2.0), $MachinePrecision], -0.5], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 56.3%

   \[\sqrt{2 \cdot {x}^{2}} \]
2. Step-by-step derivation

   1. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\left(2 \cdot {x}^{2}\right)\right) \]

   2. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left({x}^{2}\right)\right)\right) \]

   3. unpow2 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(x \cdot x\right)\right)\right) \]

   4. *-lowering-*.f64 56.3%

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{*.f64}\left(x, x\right)\right)\right) \]

3. Simplified 56.3%

   \[\leadsto \color{blue}{\sqrt{2 \cdot \left(x \cdot x\right)}} \]
4. Add Preprocessing
5. Step-by-step derivation

   1. pow1/2 N/A

      \[\leadsto {\left(2 \cdot \left(x \cdot x\right)\right)}^{\color{blue}{\frac{1}{2}}} \]

   2. associate-*r* N/A

      \[\leadsto {\left(\left(2 \cdot x\right) \cdot x\right)}^{\frac{1}{2}} \]

   3. unpow-prod-down N/A

      \[\leadsto {\left(2 \cdot x\right)}^{\frac{1}{2}} \cdot \color{blue}{{x}^{\frac{1}{2}}} \]

   4. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\left({\left(2 \cdot x\right)}^{\frac{1}{2}}\right), \color{blue}{\left({x}^{\frac{1}{2}}\right)}\right) \]

   5. pow-lowering-pow.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\left(2 \cdot x\right), \frac{1}{2}\right), \left({\color{blue}{x}}^{\frac{1}{2}}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \left({x}^{\frac{1}{2}}\right)\right) \]

   7. pow1/2 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \left(\sqrt{x}\right)\right) \]

   8. sqrt-lowering-sqrt.f64 48.5%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

6. Applied egg-rr 48.5%

   \[\leadsto \color{blue}{{\left(2 \cdot x\right)}^{0.5} \cdot \sqrt{x}} \]
7. Step-by-step derivation

   1. unpow1/2 N/A

      \[\leadsto \mathsf{*.f64}\left(\left(\sqrt{2 \cdot x}\right), \mathsf{sqrt.f64}\left(\color{blue}{x}\right)\right) \]

   2. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\left(2 \cdot x\right)\right), \mathsf{sqrt.f64}\left(\color{blue}{x}\right)\right) \]

   3. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\left(x \cdot 2\right)\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

   4. *-lowering-*.f64 48.5%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(x, 2\right)\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

8. Applied egg-rr 48.5%

   \[\leadsto \color{blue}{\sqrt{x \cdot 2}} \cdot \sqrt{x} \]
9. Step-by-step derivation

   1. sqrt-prod N/A

      \[\leadsto \left(\sqrt{x} \cdot \sqrt{2}\right) \cdot \sqrt{\color{blue}{x}} \]

   2. pow1/2 N/A

      \[\leadsto \left(\sqrt{x} \cdot {2}^{\frac{1}{2}}\right) \cdot \sqrt{x} \]

   3. *-commutative N/A

      \[\leadsto \left({2}^{\frac{1}{2}} \cdot \sqrt{x}\right) \cdot \sqrt{\color{blue}{x}} \]

   4. associate-*l* N/A

      \[\leadsto {2}^{\frac{1}{2}} \cdot \color{blue}{\left(\sqrt{x} \cdot \sqrt{x}\right)} \]

   5. metadata-eval N/A

      \[\leadsto {2}^{\left(2 \cdot \frac{1}{4}\right)} \cdot \left(\sqrt{x} \cdot \sqrt{x}\right) \]

   6. metadata-eval N/A

      \[\leadsto {2}^{\left(2 \cdot \left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)\right)} \cdot \left(\sqrt{x} \cdot \sqrt{x}\right) \]

   7. pow-sqr N/A

      \[\leadsto \left({2}^{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)} \cdot {2}^{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)}\right) \cdot \left(\color{blue}{\sqrt{x}} \cdot \sqrt{x}\right) \]

   8. pow-prod-down N/A

      \[\leadsto {\left(2 \cdot 2\right)}^{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)} \cdot \left(\color{blue}{\sqrt{x}} \cdot \sqrt{x}\right) \]

   9. metadata-eval N/A

      \[\leadsto {4}^{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)} \cdot \left(\sqrt{\color{blue}{x}} \cdot \sqrt{x}\right) \]

   10. pow-flip N/A

       \[\leadsto \frac{1}{{4}^{\frac{-1}{4}}} \cdot \left(\color{blue}{\sqrt{x}} \cdot \sqrt{x}\right) \]

   11. rem-square-sqrt N/A

       \[\leadsto \frac{1}{{4}^{\frac{-1}{4}}} \cdot x \]

   12. associate-/r/ N/A

       \[\leadsto \frac{1}{\color{blue}{\frac{{4}^{\frac{-1}{4}}}{x}}} \]

   13. /-lowering-/.f64 N/A

       \[\leadsto \mathsf{/.f64}\left(1, \color{blue}{\left(\frac{{4}^{\frac{-1}{4}}}{x}\right)}\right) \]

   14. /-lowering-/.f64 N/A

       \[\leadsto \mathsf{/.f64}\left(1, \mathsf{/.f64}\left(\left({4}^{\frac{-1}{4}}\right), \color{blue}{x}\right)\right) \]

10. Applied egg-rr 49.5%

    \[\leadsto \color{blue}{\frac{1}{\frac{{2}^{-0.5}}{x}}} \]
11. Step-by-step derivation

    1. div-inv N/A

       \[\leadsto \frac{1}{{2}^{\frac{-1}{2}} \cdot \color{blue}{\frac{1}{x}}} \]

    2. associate-/r* N/A

       \[\leadsto \frac{\frac{1}{{2}^{\frac{-1}{2}}}}{\color{blue}{\frac{1}{x}}} \]

    3. pow-flip N/A

       \[\leadsto \frac{{2}^{\left(\mathsf{neg}\left(\frac{-1}{2}\right)\right)}}{\frac{\color{blue}{1}}{x}} \]

    4. metadata-eval N/A

       \[\leadsto \frac{{2}^{\frac{1}{2}}}{\frac{1}{x}} \]

    5. pow1/2 N/A

       \[\leadsto \frac{\sqrt{2}}{\frac{\color{blue}{1}}{x}} \]

    6. clear-num N/A

       \[\leadsto \frac{1}{\color{blue}{\frac{\frac{1}{x}}{\sqrt{2}}}} \]

    7. inv-pow N/A

       \[\leadsto \frac{1}{\frac{{x}^{-1}}{\sqrt{\color{blue}{2}}}} \]

    8. sqr-pow N/A

       \[\leadsto \frac{1}{\frac{{x}^{\left(\frac{-1}{2}\right)} \cdot {x}^{\left(\frac{-1}{2}\right)}}{\sqrt{\color{blue}{2}}}} \]

    9. associate-/l* N/A

       \[\leadsto \frac{1}{{x}^{\left(\frac{-1}{2}\right)} \cdot \color{blue}{\frac{{x}^{\left(\frac{-1}{2}\right)}}{\sqrt{2}}}} \]

    10. associate-/r* N/A

        \[\leadsto \frac{\frac{1}{{x}^{\left(\frac{-1}{2}\right)}}}{\color{blue}{\frac{{x}^{\left(\frac{-1}{2}\right)}}{\sqrt{2}}}} \]

    11. inv-pow N/A

        \[\leadsto \frac{{\left({x}^{\left(\frac{-1}{2}\right)}\right)}^{-1}}{\frac{\color{blue}{{x}^{\left(\frac{-1}{2}\right)}}}{\sqrt{2}}} \]

    12. metadata-eval N/A

        \[\leadsto \frac{{\left({x}^{\left(\frac{-1}{2}\right)}\right)}^{\left(2 \cdot \frac{-1}{2}\right)}}{\frac{{x}^{\color{blue}{\left(\frac{-1}{2}\right)}}}{\sqrt{2}}} \]

    13. pow-pow N/A

        \[\leadsto \frac{{\left({\left({x}^{\left(\frac{-1}{2}\right)}\right)}^{2}\right)}^{\frac{-1}{2}}}{\frac{\color{blue}{{x}^{\left(\frac{-1}{2}\right)}}}{\sqrt{2}}} \]

    14. pow2 N/A

        \[\leadsto \frac{{\left({x}^{\left(\frac{-1}{2}\right)} \cdot {x}^{\left(\frac{-1}{2}\right)}\right)}^{\frac{-1}{2}}}{\frac{{\color{blue}{x}}^{\left(\frac{-1}{2}\right)}}{\sqrt{2}}} \]

    15. sqr-pow N/A

        \[\leadsto \frac{{\left({x}^{-1}\right)}^{\frac{-1}{2}}}{\frac{{\color{blue}{x}}^{\left(\frac{-1}{2}\right)}}{\sqrt{2}}} \]

    16. inv-pow N/A

        \[\leadsto \frac{{\left(\frac{1}{x}\right)}^{\frac{-1}{2}}}{\frac{{\color{blue}{x}}^{\left(\frac{-1}{2}\right)}}{\sqrt{2}}} \]

    17. /-lowering-/.f64 N/A

        \[\leadsto \mathsf{/.f64}\left(\left({\left(\frac{1}{x}\right)}^{\frac{-1}{2}}\right), \color{blue}{\left(\frac{{x}^{\left(\frac{-1}{2}\right)}}{\sqrt{2}}\right)}\right) \]

    18. inv-pow N/A

        \[\leadsto \mathsf{/.f64}\left(\left({\left({x}^{-1}\right)}^{\frac{-1}{2}}\right), \left(\frac{{\color{blue}{x}}^{\left(\frac{-1}{2}\right)}}{\sqrt{2}}\right)\right) \]

    19. pow-pow N/A

        \[\leadsto \mathsf{/.f64}\left(\left({x}^{\left(-1 \cdot \frac{-1}{2}\right)}\right), \left(\frac{\color{blue}{{x}^{\left(\frac{-1}{2}\right)}}}{\sqrt{2}}\right)\right) \]

    20. metadata-eval N/A

        \[\leadsto \mathsf{/.f64}\left(\left({x}^{\frac{1}{2}}\right), \left(\frac{{x}^{\color{blue}{\left(\frac{-1}{2}\right)}}}{\sqrt{2}}\right)\right) \]

    21. unpow1/2 N/A

        \[\leadsto \mathsf{/.f64}\left(\left(\sqrt{x}\right), \left(\frac{\color{blue}{{x}^{\left(\frac{-1}{2}\right)}}}{\sqrt{2}}\right)\right) \]

    22. sqrt-lowering-sqrt.f64 N/A

        \[\leadsto \mathsf{/.f64}\left(\mathsf{sqrt.f64}\left(x\right), \left(\frac{\color{blue}{{x}^{\left(\frac{-1}{2}\right)}}}{\sqrt{2}}\right)\right) \]

    23. div-inv N/A

        \[\leadsto \mathsf{/.f64}\left(\mathsf{sqrt.f64}\left(x\right), \left({x}^{\left(\frac{-1}{2}\right)} \cdot \color{blue}{\frac{1}{\sqrt{2}}}\right)\right) \]

    24. pow1/2 N/A

        \[\leadsto \mathsf{/.f64}\left(\mathsf{sqrt.f64}\left(x\right), \left({x}^{\left(\frac{-1}{2}\right)} \cdot \frac{1}{{2}^{\color{blue}{\frac{1}{2}}}}\right)\right) \]

12. Applied egg-rr 48.5%

    \[\leadsto \color{blue}{\frac{\sqrt{x}}{{\left(x \cdot 2\right)}^{-0.5}}} \]
13. Add Preprocessing

Alternative 3: 99.5% accurate, 1.0× speedup

Math

\[\begin{array}{l} x_m = \left|x\right| \\ \sqrt{x\_m} \cdot {\left(x\_m \cdot 2\right)}^{0.5} \end{array} \]

FPCore

x_m = (fabs.f64 x)
(FPCore (x_m) :precision binary64 (* (sqrt x_m) (pow (* x_m 2.0) 0.5)))

C

x_m = fabs(x);
double code(double x_m) {
	return sqrt(x_m) * pow((x_m * 2.0), 0.5);
}

Fortran

x_m = abs(x)
real(8) function code(x_m)
    real(8), intent (in) :: x_m
    code = sqrt(x_m) * ((x_m * 2.0d0) ** 0.5d0)
end function

Java

x_m = Math.abs(x);
public static double code(double x_m) {
	return Math.sqrt(x_m) * Math.pow((x_m * 2.0), 0.5);
}

Python

x_m = math.fabs(x)
def code(x_m):
	return math.sqrt(x_m) * math.pow((x_m * 2.0), 0.5)

Julia

x_m = abs(x)
function code(x_m)
	return Float64(sqrt(x_m) * (Float64(x_m * 2.0) ^ 0.5))
end

MATLAB

x_m = abs(x);
function tmp = code(x_m)
	tmp = sqrt(x_m) * ((x_m * 2.0) ^ 0.5);
end

Wolfram

x_m = N[Abs[x], $MachinePrecision]
code[x$95$m_] := N[(N[Sqrt[x$95$m], $MachinePrecision] * N[Power[N[(x$95$m * 2.0), $MachinePrecision], 0.5], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 56.3%

   \[\sqrt{2 \cdot {x}^{2}} \]
2. Step-by-step derivation

   1. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\left(2 \cdot {x}^{2}\right)\right) \]

   2. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left({x}^{2}\right)\right)\right) \]

   3. unpow2 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(x \cdot x\right)\right)\right) \]

   4. *-lowering-*.f64 56.3%

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{*.f64}\left(x, x\right)\right)\right) \]

3. Simplified 56.3%

   \[\leadsto \color{blue}{\sqrt{2 \cdot \left(x \cdot x\right)}} \]
4. Add Preprocessing
5. Step-by-step derivation

   1. pow1/2 N/A

      \[\leadsto {\left(2 \cdot \left(x \cdot x\right)\right)}^{\color{blue}{\frac{1}{2}}} \]

   2. associate-*r* N/A

      \[\leadsto {\left(\left(2 \cdot x\right) \cdot x\right)}^{\frac{1}{2}} \]

   3. unpow-prod-down N/A

      \[\leadsto {\left(2 \cdot x\right)}^{\frac{1}{2}} \cdot \color{blue}{{x}^{\frac{1}{2}}} \]

   4. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\left({\left(2 \cdot x\right)}^{\frac{1}{2}}\right), \color{blue}{\left({x}^{\frac{1}{2}}\right)}\right) \]

   5. pow-lowering-pow.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\left(2 \cdot x\right), \frac{1}{2}\right), \left({\color{blue}{x}}^{\frac{1}{2}}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \left({x}^{\frac{1}{2}}\right)\right) \]

   7. pow1/2 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \left(\sqrt{x}\right)\right) \]

   8. sqrt-lowering-sqrt.f64 48.5%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

6. Applied egg-rr 48.5%

   \[\leadsto \color{blue}{{\left(2 \cdot x\right)}^{0.5} \cdot \sqrt{x}} \]

7. Final simplification 48.5%

   \[\leadsto \sqrt{x} \cdot {\left(x \cdot 2\right)}^{0.5} \]
8. Add Preprocessing

Alternative 4: 99.5% accurate, 1.0× speedup

Math

\[\begin{array}{l} x_m = \left|x\right| \\ \sqrt{x\_m} \cdot \sqrt{x\_m \cdot 2} \end{array} \]

FPCore

x_m = (fabs.f64 x)
(FPCore (x_m) :precision binary64 (* (sqrt x_m) (sqrt (* x_m 2.0))))

C

x_m = fabs(x);
double code(double x_m) {
	return sqrt(x_m) * sqrt((x_m * 2.0));
}

Fortran

x_m = abs(x)
real(8) function code(x_m)
    real(8), intent (in) :: x_m
    code = sqrt(x_m) * sqrt((x_m * 2.0d0))
end function

Java

x_m = Math.abs(x);
public static double code(double x_m) {
	return Math.sqrt(x_m) * Math.sqrt((x_m * 2.0));
}

Python

x_m = math.fabs(x)
def code(x_m):
	return math.sqrt(x_m) * math.sqrt((x_m * 2.0))

Julia

x_m = abs(x)
function code(x_m)
	return Float64(sqrt(x_m) * sqrt(Float64(x_m * 2.0)))
end

MATLAB

x_m = abs(x);
function tmp = code(x_m)
	tmp = sqrt(x_m) * sqrt((x_m * 2.0));
end

Wolfram

x_m = N[Abs[x], $MachinePrecision]
code[x$95$m_] := N[(N[Sqrt[x$95$m], $MachinePrecision] * N[Sqrt[N[(x$95$m * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 56.3%

   \[\sqrt{2 \cdot {x}^{2}} \]
2. Step-by-step derivation

   1. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\left(2 \cdot {x}^{2}\right)\right) \]

   2. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left({x}^{2}\right)\right)\right) \]

   3. unpow2 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(x \cdot x\right)\right)\right) \]

   4. *-lowering-*.f64 56.3%

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{*.f64}\left(x, x\right)\right)\right) \]

3. Simplified 56.3%

   \[\leadsto \color{blue}{\sqrt{2 \cdot \left(x \cdot x\right)}} \]
4. Add Preprocessing
5. Step-by-step derivation

   1. pow1/2 N/A

      \[\leadsto {\left(2 \cdot \left(x \cdot x\right)\right)}^{\color{blue}{\frac{1}{2}}} \]

   2. associate-*r* N/A

      \[\leadsto {\left(\left(2 \cdot x\right) \cdot x\right)}^{\frac{1}{2}} \]

   3. unpow-prod-down N/A

      \[\leadsto {\left(2 \cdot x\right)}^{\frac{1}{2}} \cdot \color{blue}{{x}^{\frac{1}{2}}} \]

   4. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\left({\left(2 \cdot x\right)}^{\frac{1}{2}}\right), \color{blue}{\left({x}^{\frac{1}{2}}\right)}\right) \]

   5. pow-lowering-pow.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\left(2 \cdot x\right), \frac{1}{2}\right), \left({\color{blue}{x}}^{\frac{1}{2}}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \left({x}^{\frac{1}{2}}\right)\right) \]

   7. pow1/2 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \left(\sqrt{x}\right)\right) \]

   8. sqrt-lowering-sqrt.f64 48.5%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

6. Applied egg-rr 48.5%

   \[\leadsto \color{blue}{{\left(2 \cdot x\right)}^{0.5} \cdot \sqrt{x}} \]
7. Step-by-step derivation

   1. unpow1/2 N/A

      \[\leadsto \mathsf{*.f64}\left(\left(\sqrt{2 \cdot x}\right), \mathsf{sqrt.f64}\left(\color{blue}{x}\right)\right) \]

   2. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\left(2 \cdot x\right)\right), \mathsf{sqrt.f64}\left(\color{blue}{x}\right)\right) \]

   3. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\left(x \cdot 2\right)\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

   4. *-lowering-*.f64 48.5%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(x, 2\right)\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

8. Applied egg-rr 48.5%

   \[\leadsto \color{blue}{\sqrt{x \cdot 2}} \cdot \sqrt{x} \]

9. Final simplification 48.5%

   \[\leadsto \sqrt{x} \cdot \sqrt{x \cdot 2} \]
10. Add Preprocessing

Alternative 5: 99.3% accurate, 2.0× speedup

Math

\[\begin{array}{l} x_m = \left|x\right| \\ \frac{x\_m}{\sqrt{0.5}} \end{array} \]

FPCore

x_m = (fabs.f64 x)
(FPCore (x_m) :precision binary64 (/ x_m (sqrt 0.5)))

C

x_m = fabs(x);
double code(double x_m) {
	return x_m / sqrt(0.5);
}

Fortran

x_m = abs(x)
real(8) function code(x_m)
    real(8), intent (in) :: x_m
    code = x_m / sqrt(0.5d0)
end function

Java

x_m = Math.abs(x);
public static double code(double x_m) {
	return x_m / Math.sqrt(0.5);
}

Python

x_m = math.fabs(x)
def code(x_m):
	return x_m / math.sqrt(0.5)

Julia

x_m = abs(x)
function code(x_m)
	return Float64(x_m / sqrt(0.5))
end

MATLAB

x_m = abs(x);
function tmp = code(x_m)
	tmp = x_m / sqrt(0.5);
end

Wolfram

x_m = N[Abs[x], $MachinePrecision]
code[x$95$m_] := N[(x$95$m / N[Sqrt[0.5], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 56.3%

   \[\sqrt{2 \cdot {x}^{2}} \]
2. Step-by-step derivation

   1. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\left(2 \cdot {x}^{2}\right)\right) \]

   2. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left({x}^{2}\right)\right)\right) \]

   3. unpow2 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(x \cdot x\right)\right)\right) \]

   4. *-lowering-*.f64 56.3%

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{*.f64}\left(x, x\right)\right)\right) \]

3. Simplified 56.3%

   \[\leadsto \color{blue}{\sqrt{2 \cdot \left(x \cdot x\right)}} \]
4. Add Preprocessing
5. Step-by-step derivation

   1. pow1/2 N/A

      \[\leadsto {\left(2 \cdot \left(x \cdot x\right)\right)}^{\color{blue}{\frac{1}{2}}} \]

   2. associate-*r* N/A

      \[\leadsto {\left(\left(2 \cdot x\right) \cdot x\right)}^{\frac{1}{2}} \]

   3. unpow-prod-down N/A

      \[\leadsto {\left(2 \cdot x\right)}^{\frac{1}{2}} \cdot \color{blue}{{x}^{\frac{1}{2}}} \]

   4. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\left({\left(2 \cdot x\right)}^{\frac{1}{2}}\right), \color{blue}{\left({x}^{\frac{1}{2}}\right)}\right) \]

   5. pow-lowering-pow.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\left(2 \cdot x\right), \frac{1}{2}\right), \left({\color{blue}{x}}^{\frac{1}{2}}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \left({x}^{\frac{1}{2}}\right)\right) \]

   7. pow1/2 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \left(\sqrt{x}\right)\right) \]

   8. sqrt-lowering-sqrt.f64 48.5%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{pow.f64}\left(\mathsf{*.f64}\left(2, x\right), \frac{1}{2}\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

6. Applied egg-rr 48.5%

   \[\leadsto \color{blue}{{\left(2 \cdot x\right)}^{0.5} \cdot \sqrt{x}} \]
7. Step-by-step derivation

   1. unpow1/2 N/A

      \[\leadsto \mathsf{*.f64}\left(\left(\sqrt{2 \cdot x}\right), \mathsf{sqrt.f64}\left(\color{blue}{x}\right)\right) \]

   2. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\left(2 \cdot x\right)\right), \mathsf{sqrt.f64}\left(\color{blue}{x}\right)\right) \]

   3. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\left(x \cdot 2\right)\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

   4. *-lowering-*.f64 48.5%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(x, 2\right)\right), \mathsf{sqrt.f64}\left(x\right)\right) \]

8. Applied egg-rr 48.5%

   \[\leadsto \color{blue}{\sqrt{x \cdot 2}} \cdot \sqrt{x} \]
9. Step-by-step derivation

   1. sqrt-prod N/A

      \[\leadsto \left(\sqrt{x} \cdot \sqrt{2}\right) \cdot \sqrt{\color{blue}{x}} \]

   2. pow1/2 N/A

      \[\leadsto \left(\sqrt{x} \cdot {2}^{\frac{1}{2}}\right) \cdot \sqrt{x} \]

   3. *-commutative N/A

      \[\leadsto \left({2}^{\frac{1}{2}} \cdot \sqrt{x}\right) \cdot \sqrt{\color{blue}{x}} \]

   4. associate-*l* N/A

      \[\leadsto {2}^{\frac{1}{2}} \cdot \color{blue}{\left(\sqrt{x} \cdot \sqrt{x}\right)} \]

   5. metadata-eval N/A

      \[\leadsto {2}^{\left(2 \cdot \frac{1}{4}\right)} \cdot \left(\sqrt{x} \cdot \sqrt{x}\right) \]

   6. metadata-eval N/A

      \[\leadsto {2}^{\left(2 \cdot \left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)\right)} \cdot \left(\sqrt{x} \cdot \sqrt{x}\right) \]

   7. pow-sqr N/A

      \[\leadsto \left({2}^{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)} \cdot {2}^{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)}\right) \cdot \left(\color{blue}{\sqrt{x}} \cdot \sqrt{x}\right) \]

   8. pow-prod-down N/A

      \[\leadsto {\left(2 \cdot 2\right)}^{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)} \cdot \left(\color{blue}{\sqrt{x}} \cdot \sqrt{x}\right) \]

   9. metadata-eval N/A

      \[\leadsto {4}^{\left(\mathsf{neg}\left(\frac{-1}{4}\right)\right)} \cdot \left(\sqrt{\color{blue}{x}} \cdot \sqrt{x}\right) \]

   10. pow-flip N/A

       \[\leadsto \frac{1}{{4}^{\frac{-1}{4}}} \cdot \left(\color{blue}{\sqrt{x}} \cdot \sqrt{x}\right) \]

   11. rem-square-sqrt N/A

       \[\leadsto \frac{1}{{4}^{\frac{-1}{4}}} \cdot x \]

   12. associate-/r/ N/A

       \[\leadsto \frac{1}{\color{blue}{\frac{{4}^{\frac{-1}{4}}}{x}}} \]

   13. /-lowering-/.f64 N/A

       \[\leadsto \mathsf{/.f64}\left(1, \color{blue}{\left(\frac{{4}^{\frac{-1}{4}}}{x}\right)}\right) \]

   14. /-lowering-/.f64 N/A

       \[\leadsto \mathsf{/.f64}\left(1, \mathsf{/.f64}\left(\left({4}^{\frac{-1}{4}}\right), \color{blue}{x}\right)\right) \]

10. Applied egg-rr 49.5%

    \[\leadsto \color{blue}{\frac{1}{\frac{{2}^{-0.5}}{x}}} \]

11. Taylor expanded in x around 0

    \[\leadsto \color{blue}{\frac{x}{\sqrt{\frac{1}{2}}}} \]
12. Step-by-step derivation

    1. /-lowering-/.f64 N/A

       \[\leadsto \mathsf{/.f64}\left(x, \color{blue}{\left(\sqrt{\frac{1}{2}}\right)}\right) \]

    2. sqrt-lowering-sqrt.f64 49.4%

       \[\leadsto \mathsf{/.f64}\left(x, \mathsf{sqrt.f64}\left(\frac{1}{2}\right)\right) \]

13. Simplified 49.4%

    \[\leadsto \color{blue}{\frac{x}{\sqrt{0.5}}} \]
14. Add Preprocessing

Alternative 6: 99.3% accurate, 2.0× speedup

Math

\[\begin{array}{l} x_m = \left|x\right| \\ x\_m \cdot \sqrt{2} \end{array} \]

FPCore

x_m = (fabs.f64 x)
(FPCore (x_m) :precision binary64 (* x_m (sqrt 2.0)))

C

x_m = fabs(x);
double code(double x_m) {
	return x_m * sqrt(2.0);
}

Fortran

x_m = abs(x)
real(8) function code(x_m)
    real(8), intent (in) :: x_m
    code = x_m * sqrt(2.0d0)
end function

Java

x_m = Math.abs(x);
public static double code(double x_m) {
	return x_m * Math.sqrt(2.0);
}

Python

x_m = math.fabs(x)
def code(x_m):
	return x_m * math.sqrt(2.0)

Julia

x_m = abs(x)
function code(x_m)
	return Float64(x_m * sqrt(2.0))
end

MATLAB

x_m = abs(x);
function tmp = code(x_m)
	tmp = x_m * sqrt(2.0);
end

Wolfram

x_m = N[Abs[x], $MachinePrecision]
code[x$95$m_] := N[(x$95$m * N[Sqrt[2.0], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 56.3%

   \[\sqrt{2 \cdot {x}^{2}} \]
2. Step-by-step derivation

   1. sqrt-lowering-sqrt.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\left(2 \cdot {x}^{2}\right)\right) \]

   2. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left({x}^{2}\right)\right)\right) \]

   3. unpow2 N/A

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \left(x \cdot x\right)\right)\right) \]

   4. *-lowering-*.f64 56.3%

      \[\leadsto \mathsf{sqrt.f64}\left(\mathsf{*.f64}\left(2, \mathsf{*.f64}\left(x, x\right)\right)\right) \]

3. Simplified 56.3%

   \[\leadsto \color{blue}{\sqrt{2 \cdot \left(x \cdot x\right)}} \]
4. Add Preprocessing
5. Step-by-step derivation

   1. sqrt-prod N/A

      \[\leadsto \sqrt{2} \cdot \color{blue}{\sqrt{x \cdot x}} \]

   2. pow1/2 N/A

      \[\leadsto {2}^{\frac{1}{2}} \cdot \sqrt{\color{blue}{x \cdot x}} \]

   3. sqrt-prod N/A

      \[\leadsto {2}^{\frac{1}{2}} \cdot \left(\sqrt{x} \cdot \color{blue}{\sqrt{x}}\right) \]

   4. rem-square-sqrt N/A

      \[\leadsto {2}^{\frac{1}{2}} \cdot x \]

   5. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\left({2}^{\frac{1}{2}}\right), \color{blue}{x}\right) \]

   6. pow1/2 N/A

      \[\leadsto \mathsf{*.f64}\left(\left(\sqrt{2}\right), x\right) \]

   7. sqrt-lowering-sqrt.f64 49.4%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{sqrt.f64}\left(2\right), x\right) \]

6. Applied egg-rr 49.4%

   \[\leadsto \color{blue}{\sqrt{2} \cdot x} \]

7. Final simplification 49.4%

   \[\leadsto x \cdot \sqrt{2} \]
8. Add Preprocessing

Reproduce

herbie shell --seed 2024152 
(FPCore (x)
  :name "sqrt D (should all be same)"
  :precision binary64
  (sqrt (* 2.0 (pow x 2.0))))